Chao Wu is currently an Associate Professor in Nanjing University of Science and Technology. He used to be a Post-doctoral researcher in Northeastern University under the supervision of Prof. Yanzhi Wang. He received his Ph.D. degree in Computer Science with City University of Hong Kong under the supervision of Prof. Chun Jason Xue. He has two master degrees, one in IC Design with HKUST and the other one in Detect Technology and Automation Instruments with Tongji University.

My research topics include AI Acceleration, Storage Architecture and File System.

(C18) Chao Wu, Cheng Ji, Congming Gao, Weichao Guo, Chao Yu, Linwei Zhu, Yanzhi Wang, “DeltaFS: Low Update Overhead with Delta-inlining for Log-structured File System on Mobile Devices”. (arxiv.org/abs/2210.04623)

(C17) Jun Liu, Chao Wu, Changdi Yang, Hao Tang, Haoye Dong, Zhenglun Kong, Geng Yuan, Wei Niu, Dong Huang, Yanzhi Wang, “Efficient Pruning of Large Language Model with Adaptive Estimation Fusion”. (arxiv.org/abs/2403.10799)

(C16) Sheng Li, Geng Yuan, Yawen Wu, Yue Dai, Chao Wu, Alex K. Jones, Jingtong Hu, Yanzhi Wang, Xulong Tang, “EdgeOL: Efficient in-situ Online Learning on Edge Devices”. (arxiv.org/abs/2401.16694)

(C15) Yushu Wu, Yifan Gong, Zheng Zhan, Geng Yuan, Yanyu Li, Qi Wang, Chao Wu, Yanzhi Wang, “MOC: Multi-Objective Mobile CPU-GPU Co-Optimization for Power-Efficient DNN Inference”. (Proceedings of the 42st IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2023) )(Corresponding author)

(C14) Xuan Shen, Peiyan Dong, Lei Lu, Zhenglun Kong, Zhengang Li, Ming Lin, Chao Wu, Yanzhi Wang, “Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge”. (Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2024) )

(C13) Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, et al, “All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management”. (Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2022) )

(C12) Sheng Li, Chao Wu, Ao Li, Yanzhi Wang, Xulong Tang, Geng Yuan, “Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning”. (The Twelfth International Conference on Learning Representations (ICLR 2024) )

(C11) Peiyan Dong, LEI LU, Chao Wu, Cheng Lyu, Geng Yuan, Hao Tang, Yanzhi Wang, “PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile”. (Advances in Neural Information Processing Systems 36 (NeurIPS 2023) )(Corresponding author)

(C10) Mengquan Li, Chao Wu, et al, “RLAlloc: A Deep Reinforcement Learning-Assisted Resource Allocation Framework for Enhanced Both I/O Throughput and QoS Performance of Multi-Streamed SSDs”. (Design Automation Conference (DAC'23))(Co-first and corresponding author)

(C9) Yifan Gong, Pu Zhao, Zhen Zhan, Yushu Wu, Chao Wu, et al, “Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge”. (Design Automation Conference (DAC'23))(Corresponding author)

(C8) Chao Wu, Yufei Cui, Cheng Ji, Teiwei Kuo, Chun Jason Xue. "Pruning Deep Reinforcement Learning for Dual User Experience and Storage Lifetime Improvement on Mobile Devices" (2020 International Conference On Embedded Software (EMSOFT).)

(C7) Chao Wu, Qiao Li, Cheng Ji, Teiwei Kuo, Chun Jason Xue. "Boosting User Experience via Foreground-Aware Cache Management in UFS Mobile Devices" (2020 International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES).)

(C6) Cheng Ji, Li-ping Chang, Riwei Pan, Chao Wu, Congming Gao, Liang Shi, Tei-wei Kuo, Chun Jason Xue. “Pattern-guided File Compression with User Experience Enhancement for Log-structured File System on Mobile Devices”. (9th USENIX Conference on File and Storage Technologies (FAST’2021).) to appear

(C5) Chao Wu, Cheng Ji, Liang Shi, Chun Jason Xue, Yuangang Wang. “Dynamic merging/splitting for better responsiveness in mobile devices”. (2016 5th Non-Volatile Memory Systems and Applications Symposium (NVMSA).IEEE, 2016.)

(C4) Chao Wu, Cheng Ji, Chun Jason Xue. “Reinforcement Learning-based Background Segment Cleaning for Log-structured File System on Mobile Devices”. (2019 IEEE International Conference on Embedded Software and Systems (ICESS).)

(C3) Chao Wu, Cheng Ji, Qiao Li, Chenchen Fu, Chun Jason Xue. “Maximizing I/O throughput and minimizing performance variation via reinforcement learning based I/O merging for SSDs: work-in-progress”. (2018 International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES).)

(C2) Cheng Ji, Chao Wu, Li-Pin Chang, Liang Shi, Chun Jason Xue. “I/O scheduling with mapping cache awareness for flash-based storage systems”. (The 7th IEEE Non-Volatile Memory Systems and Applications Symposium NVMSA'18, August, 2018.)

(C1) Cheng Ji, Li-Pin Chang, Liang Shi, Chao Wu, Qiao Li, Chun Jason Xue. “An Empirical Study of File-System Fragmentation in Mobile Storage Systems”, (The 2016 USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage).)

(J8) Chao Wu, Yufei Cui, Cheng Ji, Teiwei Kuo, Chun Jason Xue, “Pruning Deep Reinforcement Learning for Dual User Experience and Storage Lifetime Improvement on Mobile Devices”. (IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2020).)

(J7) Chao Wu, Qiao Li, Cheng Ji, Teiwei Kuo, Chun Jason Xue, “Boosting User Experience via Foreground-Aware Cache Management in UFS Mobile Devices”. (IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2020).)

(J6) Chao Wu, Cheng Ji, Qiao Li, Congming Gao, Riwei Pan, Chenchen Fu,Liang Shi, Chun Jason Xue， “Maximizing I/O Throughput and Minimizing Performance Variation via Reinforcement Learning Based I/O Merging for SSDs”. (IEEE Trans. Computers 69(1): 72-86 (2020).)

(J5) Zongwei Zhu, Chao Wu, Cheng Ji, Xiamin Wang, “Machine Learning Assisted OSP Approach for Improved QoS Performance on 3D Charge-Trap Based SSDs”. (International Journal of Intelligent Systems (IF:10.31), 2020 (Corresponding Author).)

(J4) Mengquan Li, Kenli Li, Chao Wu, Gang Liu, Mingfeng Lan, Yunchuan Qin, Zhuo Tang, Weichen Liu, “Automated Optical Accelerator Search Toward Superior Acceleration Efficiency, Inference Robustness, and Development Speed”. (IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2024) (Corresponding Author).)

(J3) Yangmei Zhang, Fanfan Shen, Mengquan Li, Chao Wu, “Predicting for I/O stack optimizations on cyber–physical systems”. (Microprocessors and Microsystems (2023))

(J2) Cheng Ji, Li-Pin Chang, Chao Wu, Liang Shi, Chun Jason Xue, “An I/O Scheduling Strategy for Embedded Flash Storage Devices with Mapping Cache”. (IEEE Trans. on CAD of Integrated Circuits and Systems 37(4): 756-769 (2018).)

(J1) Cheng Ji, Li-Pin Chang, Liang Shi, Congming Gao, Chao Wu, Yuangang Wang, Chun Jason Xue, “Lightweight Data Compression for Mobile Flash Storage”. (ACM Trans. Embedded Comput. Syst. 16(5s): 183:1-183:18 (2017).)

• Services as TPC in "ICCAD" (2024)
• Services as TPC in "APWeb" (2024)
• Services as Session Chair in "GLSVLSI" (2023)
• Services as Session Chair in "ASP-DAC" (2023)
• Services as TPC in "ICCAD" (2023)

• 2024.05-2025.05 Large Pre-trained Model optimization on distributed system (Joint Project by NJUST and Hansui Co.ltd).
• 2021.12-2024.12 On Intelligent I/O Stack Optimization (National Science Foundation, Youth Fund).
• 2019.11-2020.10 Local file system united optimization (Joint Project by City University of Hong Kong and Huawei Co.ltd).
• 2014.12-2016.06 Android OS kernel Optimization (Joint Project by City University of Hong Kong and Huawei Co.ltd).
• 2013.09-2014.11 3D camera-based low cost hand tracking devices development (project in ASTRI).
• 2012.10-2013.09 IR/CMOS sensor-based optical touch screen development (project in ASTRI).
• 2012.01-2012.07 Feature motion decorrelation in ultrasound pattern tracking (Final project in HKUST).